Systemic ALK-negative anaplastic large cell lymphoma: Insights into morphologic, immunophenotypic, genetic and molecular characteristics.

Anaplastic large cell lymphoma (ALCL) is a mature T-cell neoplasm characterized by large pleomorphic cells, often with horseshoe- or kidney-shaped nuclei and abundant cytoplasm (hallmark cells), and uniformly strong CD30 expression. Based on ALK expression or ALK rearrangement, ALCL is further classified into ALK-positive (ALK+) and ALK-negative types. This review focuses on the clinicopathologic, immunophenotypic, cytogenetic and molecular features of systemic ALK-negative ALCL. These patients are usually older adults who present with advanced stage disease and often a poor prognosis. ALK-negative ALCL is morphologically indistinguishable from the common pattern of ALK+ ALCL, but some cases show non-common morphology, such as "donut cells", Hodgkin-like features. ALK-negative ALCL is often negative for T-cell antigens (so-called "antigen loss") and in some cases can have a "null" immunophenotype and be confused with other hematopoietic and non-hematopoietic neoplasms. Recurrent genetic/molecular alterations have been identified in systemic ALK-negative ALCL, including rearrangements of DUSP22, TP63, JAK2, FRK, MYC, ROS1 and TYK2; mutations of JAK1, STAT3 and MSCE; and aberrant expression of ERBB4. Some of these alterations may have prognostic significance and/or provide potential therapeutic targets. Data support the idea that ALK-negative ALCL with DUSP22 rearrangement is a distinctive variant due to its unique morphologic, immunophenotypic and molecular features. Gene expression profiling data have shown that ALK-negative ALCL has distinctive molecular signatures, different from ALK+ ALCL and other T-cell lymphomas. Better understanding of the morphologic, immunophenotypic, genetic and molecular features of ALK-negative ALCL will help establish the correct diagnosis, guide therapeutic strategies and improve patient outcomes.

Synergistic integration of MXene nanostructures into electrospun fibers for advanced biomedical engineering applications.

MXene-based architectures have paved the way in various fields, particularly in healthcare area, owing to their remarkable physiochemical and electromagnetic characteristics. Moreover, the modification of MXene structures and their combination with polymeric networks have gained considerable prominence to further develop their features. The combination of electrospun fibers with MXenes would be promising in this regard since electrospinning is a well-established technique that is now being directed toward commercial biomedical applications. The introduction of MXenes into electrospun fibrous frameworks has highlighted outcomes in various biomedical applications, including cancer therapy, controlled drug delivery, antimicrobial targets, sensors, and tissue engineering. Correspondingly, this review describes the employed strategies for the preparation of electrospun configurations in tandem with MXene nanostructures with remarkable characteristics. Next, the advantages of MXene-decorated electrospun fibers for use in biomedical applications are comprehensively discussed. According to the investigations, rich surface functional groups, hydrophilicity, large surface area, photothermal features, and antimicrobial and antibacterial activities of MXenes could synergize the performance of electrospun layers to engineer versatile biomedical targets. Moreover, the future of this path is clarified to combat the challenges related to the electrospun fibers decorated with MXene nanosheets.

Recent insights on MXene-based architectures for monitoring and sensing of gaseous pollutants: A review.

Epidemiology and public health concerns have primarily relied on the accurate control of gas pollutants, requiring highly efficient gas sensor devices for detecting hazardous gases. Despite the dedication of many efforts in this era, the precise, continuous scrutiny of gases remains elusive for appropriate gas selectivity, prompt response and recovery time, proper repeatability, as well as low cost. Accordingly, nanostructured architectural sensing cues have received enormous attention toward versatile detection and sensing procedures. As a representational nanostructure, the MXene family has been widely introduced to tailor and augment sensor patterns by providing large surface area, tunable surface chemistry, superior electrical conductivity, chemical stability, compatibility with flexible substrates, and potential for multifunctionality. Additionally, they could be synthesized in various formations of film and layered designs, fibrous membranes, and gel-like structures, creating synergetic effects that can provide superior gas-sensing performance. Herein, the synthesis and benefits of MXene nanosheets as gas-sensitive materials, in tandem with the past-to-present progress of MXene-based gas sensors in the formation of films, fibrous, and gel-like configurations, are comprehensively reviewed. As an in-depth reference, the present overview could shed light on further advancing gas sensor architectures developed based on MXene structures.

A multifunctional sensor for detecting tetracycline, 4-nitrophenol, and pesticides.

In recent years, due to the abuse of antibiotics, nitro explosives and pesticides, which have caused great harm to the environment and human health, social concerns have prompted researchers to develop more sensitive detection platforms for these pollutants. In this paper, a novel two-dimensional Zn (II) coordination polymer, [Zn(L)0.5(1,2-bimb)]·DMF (1), [H4L=[1,1':4',1''-terphenyl]-2, 2'',4, 4'' -tetracarboxylic acid, 1,2-bimb = 1,2-bis(imidazol-1-ylmethyl)benzene] was synthesized using a hydro-solvothermal method. Among commonly used organic solvents, 1 exhibits significant stability. Fast and efficient fluorescence response can be achieved for tetracycline (TET), 4-nitrophenol (4-NP), fluazinam (FLU), and abamectin benzoate (AMB) with low detection limits. A binary intelligent logic gate device with FLU and AMB as chemical input signals is successfully constructed, which provides a new idea for biochemical detection. In addition, a portable visual test paper has been prepared, which has high sensitivity, good selectivity, and simple operation. It can be used for rapid detection of pollutants in daily life and has broad application prospects. Finally, a detailed discussion was conducted on the fluorescence sensing mechanism of 1 for detecting TET, 4-NP, AMB and FLU.

Performance Evaluation of a Novel Artificial Intelligence-Assisted Digital Microscopy System for the Routine Analysis of Bone Marrow Aspirates.

Bone marrow aspiration (BMA) smear analysis is essential for diagnosis, treatment, and monitoring of a variety of benign and neoplastic hematological conditions. Currently, this analysis is performed by manual microscopy. We conducted a multicenter study to validate a computational microscopy approach with an artificial intelligence-driven decision support system. A total of 795 BMA specimens (615 Romanowsky-stained and 180 Prussian blue-stained) from patients with neoplastic and other clinical conditions were analyzed, comparing the performance of the Scopio Labs X100 Full Field BMA system (test method) with manual microscopy (reference method). The system provided an average of 1,385 ± 536 (range, 0-3,131) cells per specimen for analysis. An average of 39.98 ± 19.64 fields of view (range, 0-140) per specimen were selected by the system for analysis, of them 87% ± 21% (range, 0%-100%) were accepted by the qualified operators. These regions were included in an average of 17.62 ± 7.24 regions of interest (range, 1-50) per specimen. The efficiency, sensitivity, and specificity for primary and secondary marrow aspirate characteristics (maturation, morphology, and count assessment), as well as overall interuser agreement, were evaluated. The test method showed a high correlation with the reference method for comprehensive BMA evaluation, both on Romanowsky- (90.85% efficiency, 81.61% sensitivity, and 92.88% specificity) and Prussian blue-stained samples (90.0% efficiency, 81.94% sensitivity, and 93.38% specificity). The overall agreement between the test and reference methods for BMA assessment was 91.1%. For repeatability and reproducibility, all standard deviations and coefficients of variation values were below the predefined acceptance criteria both for discrete measurements (coefficient of variation below 20%) and differential measurements (SD below 5%). The high degree of correlation between the digital decision support system and manual microscopy demonstrates the potential of this system to provide a high-quality, accurate digital BMA analysis, expediting expert review and diagnosis of BMA specimens, with practical applications including remote BMA evaluation and possibly new opportunities for the research of normal and neoplastic hematopoiesis.

Functional vertical connectivity of microbial communities in the ocean.

Sinking particles are a critical conduit for the transport of surface microbes to the ocean's interior. Vertical connectivity of phylogenetic composition has been shown; however, the functional vertical connectivity of microbial communities has not yet been explored in detail. We investigated protein and taxa profiles of both free-living and particle-attached microbial communities from the surface to 3000 m depth using a combined metaproteomic and 16S rRNA amplicon sequencing approach. A clear compositional and functional vertical connectivity of microbial communities was observed throughout the water column with Oceanospirillales, Alteromonadales, and Rhodobacterales as key taxa. The surface-derived particle-associated microbes increased the expression of proteins involved in basic metabolism, organic matter processing, and environmental stress response in deep waters. This study highlights the functional vertical connectivity between surface and deep-sea microbial communities via sinking particles and reveals that a considerable proportion of the deep-sea microbes might originate from surface waters and have a major impact on the biogeochemical cycles in the deep sea.

Effectiveness and safety of glucagon-like peptide 1 receptor agonists in patients with type 2 diabetes: evidence from a retrospective real-world study.

Introduction: Global phase III clinical trials have shown superior hypoglycemic efficacy to insulin and other oral hypoglycemic agents. However, there is a scarcity of real-world data comparing different glucagon-like peptide 1 receptor agonist (GLP-1RA) directly. This study aimed to assess the safety and effectiveness of various GLP-1RA in treating type 2 diabetes mellitus (T2DM) in a real-world clinical setting and identify predictive factors for favorable treatment outcomes. Methods: This was a retrospective, single-center, real-world study. The changes in HbA1c, fasting plasma glucose (FPG), body weight, systolic blood pressure (SBP), diastolic blood pressure (DBP), and the percentage of participants who achieved HbA1c of <7%, 7%-8%, and ≥ 8% after GLP-1RA treatment was analyzed. The clinical factors that affect the effectiveness of GLP-1RA were analyzed. Results: At baseline, the 249 participants had a mean baseline HbA1c of 8.7 ± 1.1%. After at least three months of follow-up, the change in HbA1c was -0.89 ± 1.3% from baseline. Dulaglutide exerted a more significant hypoglycemic effect than immediate-release exenatide. The percentage of participants who achieved HbA1c<7% was substantial, from 6.0% at baseline to 28.9%. Average body weight decreased by 2.02 ± 3.8 kg compared to baseline. After GLP-1RA treatment, the reduction in SBP was 2.4 ± 7.1 mmHg from baseline. A shorter duration of diabetes and a higher baseline HbA1c level were more likely to achieve a good response in blood glucose reduction. Conclusions: This study provided real-world evidence showing that GLP-1RA significantly improved HbA1c, body weight, and SBP. The results can inform the decision-making about GLP-1RA treatment in daily clinical practice.

Validation of Artificial Intelligence (AI)-Assisted Flow Cytometry Analysis for Immunological Disorders.

Flow cytometry is a vital diagnostic tool for hematologic and immunologic disorders, but manual analysis is prone to variation and time-consuming. Over the last decade, artificial intelligence (AI) has advanced significantly. In this study, we developed and validated an AI-assisted flow cytometry workflow using 379 clinical cases from 2021, employing a 3-tube, 10-color flow panel with 21 antibodies for primary immunodeficiency diseases and related immunological disorders. The AI software (DeepFlow™, version 2.1.1) is fully automated, reducing analysis time to under 5 min per case. It interacts with hematopatholoists for manual gating adjustments when necessary. Using proprietary multidimensional density-phenotype coupling algorithm, the AI model accurately classifies and enumerates T, B, and NK cells, along with important immune cell subsets, including CD4+ helper T cells, CD8+ cytotoxic T cells, CD3+/CD4-/CD8- double-negative T cells, and class-switched or non-switched B cells. Compared to manual analysis with hematopathologist-determined lymphocyte subset percentages as the gold standard, the AI model exhibited a strong correlation (r > 0.9) across lymphocyte subsets. This study highlights the accuracy and efficiency of AI-assisted flow cytometry in diagnosing immunological disorders in a clinical setting, providing a transformative approach within a concise timeframe.

Combined ATAC-seq, RNA-seq, and GWAS analysis reveals glycogen metabolism regulatory network in Jinjiang oyster ( Crassostrea ariakensis).

Glycogen serves as the principal energy reserve for metabolic processes in aquatic shellfish and substantially contributes to the flavor and quality of oysters. The Jinjiang oyster ( Crassostrea ariakensis) is an economically and ecologically important species in China. In the present study, RNA sequencing (RNA-seq) and assay for transposase-accessible chromatin using sequencing (ATAC-seq) were performed to investigate gene expression and chromatin accessibility variations in oysters with different glycogen contents. Analysis identified 9 483 differentially expressed genes (DEGs) and 7 215 genes with significantly differential chromatin accessibility (DCAGs) were obtained, with an overlap of 2 600 genes between them. Notably, a significant proportion of these genes were enriched in pathways related to glycogen metabolism, including "Glycogen metabolic process" and "Starch and sucrose metabolism". In addition, genome-wide association study (GWAS) identified 526 single nucleotide polymorphism (SNP) loci associated with glycogen content. These loci corresponded to 241 genes, 63 of which were categorized as both DEGs and DCAGs. This study enriches basic research data and provides insights into the molecular mechanisms underlying the regulation of glycogen metabolism in C. ariakensis.

Evolution of SARS-CoV-2 Viral Mutations in Individuals with Prolonged Infections.

OBJECTIVE: The world has been faced with the repeat rise of SARS-CoV-2 variants since late 2020, including Alpha, Beta, Gamma, Delta, and the latest simultaneous emergence of far-flung spawn of Omicron sub-lineages in different parts of the globe. This has brought us the challenge of determining what factor(s) have been the selective force behind these immune evasive and therapy resistant mutations. It is very possible that such variants evolved in limited host individuals with prolonged infections, or from a localized community of patients. METHODS: This study surveys the GISAID time capsule of mutations found in viral genomes from patients with prolonged same lineage viral infections. We analyzed 288 SARS-CoV-2 genomes representing 113 patients who had same lineage viral genomes in two or more samples stored in GISAID. RESULTS: Of these, thirty-five (30.9%) of the 113 patients developed mutations during their infections. Samples from patients whose viral genomes showed nucleotide changes(s) (n=35) versus those that showed no change (n=78) had a statistically significant difference (p=2.121x10-4) in duration of infection by a median of 13 days (range 0-109 days) versus 6 days (range 0-72 days), respectively. Five highly recognizable variant-defining mutations with immune evasion properties were identified in 5 cases infected by the B.1 lineages in late 2020 and early 2021. CONCLUSION: This suggests the duration of infection is a contributing factor that gives rise to mutations, but not the sole factor, and individual host conditions may play a critical role in driving viral evolution.

Immunological dynamic characteristics in acute myeloid leukemia predict the long-term outcomes and graft-versus host-disease occurrences post-transplantation.

To investigate the relationship between immune dynamic and graft-versus-host-disease (GVHD) risk, 111 initial diagnostic acute myeloid leukemia patients were reviewed. The flow cytometry data of 12 major lymphocyte subsets in bone marrow (BM) from 60 transplant patients at four different time points were analyzed. Additionally, 90 immune subsets in peripheral blood (PB) of 11 post-transplantation on day 100 were reviewed. Our results demonstrated that transplant patients had longer OS compared to non-transplant patients (P < 0.001). Among transplant patients, those who developed GVHD showed longer OS than those without GVHD (P < 0.05). URD donors and CMV-negative status donors were associated with improved OS in transplant patients (P < 0.05). Importantly, we observed a decreased Th/Tc ratio in BM at initial diagnostic in patients with GVHD compared to those without GVHD (P = 0.034). Receiver operating characteristic analysis indicated that a low Th/Tc ratio predicted an increased risk of GVHD with a sensitivity of 44.44% and specificity of 87.50%. Moreover, an increased T/NK ratio in BM of post-induction chemotherapy was found to be associated with GVHD, with a sensitivity of 75.76% and specificity of 65.22%. Additionally, we observed a decreased percentage of NK1 (CD56-CD16+NK) in PB on day 100 post-transplantation in the GVHD group (P < 0.05). These three indicators exhibit promising potential as specific and useful biomarkers for predicting GVHD. These findings provide valuable insights for the early identification and management of GVHD risk, thereby facilitating the possibility of improving patient outcomes.

Cytogenetically Cryptic Acute Promyelocytic Leukemia: A Diagnostic Challenge.

Cytogenetically cryptic acute promyelocytic leukemia (APL) is rare, characterized by typical clinical and morphological features, but lacks t(15;17)(q24;q21)/PML::RARA translocation seen in conventional karyotyping or FISH. The prompt diagnosis and treatment of APL are critical due to life-threatening complications associated with this disease. However, cryptic APL cases remain a diagnostic challenge that could mislead the appropriate treatment. We describe four cryptic APL cases and review reported cases in the literature. Reverse transcriptase polymerase chain reaction (RT-PCR) is the most efficient diagnostic modality to detect these cases, and alternative methods are also discussed. This study highlights the importance of using parallel testing methods to diagnose cryptic APL cases accurately and effectively.

Three-dimensional model construction and wind simulation of different tree species in farmland shelter.

Protective forests are the ecological barriers of oases in arid sand areas and can effectively prevent and control wind and sand hazards. The structural characteristics of individual trees, as the basic unit of protective forests, are the key factors affecting the protective benefits. With the typical leafless tree species of Ulan Buh Desert oasis, i.e., Populus alba var. pyramidalis, Populus nigra var. thevestina, and Populus popularis, as the research objects, and by using the ground-based LiDAR and through computational fluid dynamics (CFD), we fully explored the structural characteristics of individual trees and their surrounding aerodynamic characteristics on the basis of real 3D models. We further established the relationship between structural parameters of individual trees and wind field index. The results showed that combining AdQSM and MeshLab to build tree models had high accuracy. The wind field around the individual trees could be roughly divided into six regions, including the attenuation zone of the windward side of the plant, the acceleration zone at the top of the plant, the eddy zone, the calm zone, the transition zone, and the recovery zone of leeward side of the plant. The pressure field around individual trees showed a gradual change of high pressure on the windward side to low pressure on the leeward side. Horizontally, in the range of 20% to 50% reduction in relative wind speed, the effective protection distances were 0.21H-1.51H, 0.20H-0.91H, and 0.25H-1.64H (H was the corresponding tree height) for P. alba var. pyramidalis, P. nigra var. thevestina, and P. popularis, corresponding to effective protection areas of 18-294, 15-227, and 18-261 m2, respectively. The maximum wind speed decay rate in the vertical direction was at 0.3H height for P. alba var. pyramidalis and P. popularis, and was reflected at 0.5H height for P. nigra var. thevestina. The correlation and stepwise regression analysis of the single tree structure parameters with the wind field indicators clearly indicated that optical porosity and volume porosity dominated the protection effect. Among the wind field factors, the best regression models related to the porous coefficient were screened for three factors, including diameter at breast height, tree surface area, and optical porosity. The regression variables screened for effective protection distance and effective protection area differed among the classes.

Patient-Specific Targeting of the T-Cell Receptor Variable Region as a Therapeutic Strategy in Clonal T-Cell Diseases.

PURPOSE: Targeted therapeutics are a goal of medicine. Methods for targeting T-cell lymphoma lack specificity for the malignant cell, leading to elimination of healthy cells. The T-cell receptor (TCR) is designed for antigen recognition. T-cell malignancies expand from a single clone that expresses one of 48 TCR variable beta (Vß) genes, providing a distinct therapeutic target. We hypothesized that a mAb that is exclusive to a specific Vß would eliminate the malignant clone while having minimal effects on healthy T cells. EXPERIMENTAL DESIGN: We identified a patient with large granular T-cell leukemia and sequenced his circulating T-cell population, 95% of which expressed Vß13.3. We developed a panel of anti-Vß13.3 antibodies to test for binding and elimination of the malignant T-cell clone. RESULTS: Therapeutic antibody candidates bound the malignant clone with high affinity. Antibodies killed engineered cell lines expressing the patient TCR Vß13.3 by antibody-dependent cellular cytotoxicity and TCR-mediated activation-induced cell death, and exhibited specific killing of patient malignant T cells in combination with exogenous natural killer cells. EL4 cells expressing the patient's TCR Vß13.3 were also killed by antibody administration in an in vivo murine model. CONCLUSIONS: This approach serves as an outline for development of therapeutics that can treat clonal T-cell-based malignancies and potentially other T-cell-mediated diseases. See related commentary by Varma and Diefenbach, p. 4024.

Assessment on the declining degree of farmland shelter forest in a desert oasis based on LiDAR and hyperspectrum imagery.

We examined the growth decline and health status of farmland protective forest belt (Populus alba var. pyramidalis and Populus simonii shelterbelts) in Ulanbuh Desert Oasis by using airborne hyperspectral and ground-based LiDAR to collect the hyperspectral images and point cloud data of the whole forest belt respectively. Through correlation analysis and stepwise regression analysis, we constructed the evaluation model of the decline degree of farmland protection forest with the spectral differential value, vegetation index, and forest structure parameters as independent variables and the tree canopy dead branch index of the field survey as dependent variables. We further tested the accuracy of the model. The results showed that the evaluation accuracy of the decline degree of P. alba var. pyramidalis and P. simonii by LiDAR method was better than that by hyperspectral method, and that the evaluation accuracy of the combined LiDAR and hyperspectral method was the highest. Using the LiDAR method, hyperspectral method, the combined method, the optimal model of P. alba var. pyramidalis was all light gradient boosting machine model, with the overall classification accuracy being 0.75, 0.68, 0.80, and Kappa coefficient being 0.58, 0.43, 0.66, respectively. The optimal model of P. simonii was random forest model, random forest model, and multilayer perceptron model, with the overall classification accuracy being 0.76, 0.62, 0.81, and Kappa coefficient being 0.60, 0.34, 0.71, respectively. This research method could accurately check and monitor the decline of plantations.

Construction of 3D sheet-packed hierarchical MoS2/BiOBr heterostructures with remarkably enhanced photocatalytic performance for tetracycline and levofloxacin degradation.

In this paper, MoS2 nanosheets were prepared and deposited on BiOBr microflowers through deposition-hydrothermal strategy. MoS2 exhibited a string of nanosheets with wrinkled layer outlook, and MoS2/BiOBr composites displayed a micro-flower morphology with the diameter of 2-3 µm. Visible-light harvesting performance was significantly improved in the region of 400-600 nm for MoS2/BiOBr. The obtained MoS2/BiOBr samples exhibited tremendous enhanced catalytic activity, which could degrade 92.96% of tetracycline and 90.31% of levofloxacin within 70 min. The photo-generated holes and ⋅OH radicals played the dominant roles in the whole photocatalytic decomposition process. Based on the analysis of DRS, BET, PL, and electrochemical results, the remarkably improved photocatalytic performance may be ascribed to the synergistic effect of strong visible-light harvesting ability, enhanced BET surface area, and faster separation or transfer efficiency of photo-generated charges.

Phylogenetic analyses of 41 Y-STRs and machine learning-based haplogroup prediction in the Qingdao Han population from Shandong province, Eastern China.

BACKGROUND: Known for its rich history and culture, Qingdao is a typical symbol of Chinese maritime culture. Its unique genetic landscape has aroused interest among geneticists and forensic scientists. However, the genetic landscape of Qingdao has never been uncovered. AIM: This investigation intends to provide light on Qingdao's paternal genetic diversity and its evolutionary connections to other Han subgroups. SUBJECTS AND METHODS: The genetic polymorphisms of 41 Y-chromosomal short tandem repeat (STR) loci in the Qingdao Han were investigated using SureID® PathFinder Plus Kit. Phylogenetic studies were performed using genotype data from 52 East Asian groups at 23 common Y-STR loci. A multidimensional scaling plot and cladogram were constructed. Linear Discriminant Analysis (LDA) was carried out for predicting categories among the Han people. The k-nearest neighbour (kNN) algorithm was utilised to designate Y-SNP haplogroups for each haplotype. RESULTS: The Qingdao Han were genetically far from the Tibeto-Burman populations and close with the Han people from northern China. LDA indicated a deep integration among the present-day Han people. By the kNN model, the predicted O2a2 and O2a1 were shown to be the predominant Y-SNP haplogroups. CONCLUSIONS: This study would be helpful for reconstructing the patrilineal history in China and establishing a more comprehensive Y-STR database.

Upregulation of KLF14 expression attenuates kidney fibrosis by inducing PPARα-mediated fatty acid oxidation.

Tubulointerstitial fibrosis (TIF) is essential during the development of end-stage kidney disease (ESKD) and is associated with the impairment of fatty acid oxidation (FAO). Kruppel-like factor 14 (KLF14) is an important gene in lipid metabolism, but its role in TIF remains unknown. TGF-ß-stimulated HK-2 cells and mouse unilateral ureteral obstruction (UUO) were used as renal fibrosis models. The role of KLF14 in the process of renal fibrosis was verified by gene knockout mice, genetic or pharmacological interference in animal model and cell model respectively. In the current study, we found that KLF14 expression increased after activation of the TGF-ß signaling pathway during TIF. In KLF14-/- mice, more severe fibrosis was observed after unilateral ureteral obstruction (UUO) was induced. In human HK2 cells, knockdown of KLF14 led to more severe fibrosis induced by TGF-ß1, while overexpression of KLF14 partially attenuated this process. Specifically, KLF14 deficiency decreased mitochondrial FAO activity, resulting in lipid accumulation. Thus, the energy supply to the cells was insufficient, finally resulting in TIF. We further proved that KLF14 could target peroxisome proliferator activated receptor alpha (PPARα) as a transcriptional activator. This study identified the upregulation of KLF14 expression in response to kidney stress during the process of fibrosis. Upon TIF, the activated TGF-ß signaling pathway can enhance KLF14 expression, while the upregulation of KLF14 expression can decrease the degree of TIF by improving FAO activity in tubular epithelial cells and recovering the energy supply mediated by PPARα.

Programmable Thermo-Responsive Actuation of Hydrogels via Light-Guided Surface Growth of Active Layers on Shape Memory Substrates.

Hydrogel shape memory and actuating functionalities are heavily pursued and have found great potential in various application fields. However, their combination for more flexible and complicated morphing behaviors is still challenging. Herein, it is reported that by controlling the light-initiated polymerization of active hydrogel layers on shape memory hydrogel substrates, advanced morphing behaviors based on programmable hydrogel shapes and actuating trajectories are realized. The formation and photo-reduction-induced dissociation of Fe3+ -carboxylate coordination endow the hydrogel substrates with the shape memory functionality. The photo-reduced Fe2+ ions can diffuse from the substrates into the monomer solutions to initiate the polymerization of the thermally responsive active layers, whose actuating temperatures and amplitudes can be facially tuned by controlling their thicknesses and compositions. One potential application, a shape-programmable 3D hook that can lift an object with a specific shape, is also unveiled. The demonstrated strategy is extendable to other hydrogel systems to realize more versatile and complicated actuating behaviors.

A mixed blessing for liver transplantation patients - Rapamycin.

BACKGROUND: Liver transplantation (LT) is an effective treatment option for end-stage liver disease. Mammalian target of rapamycin (mTOR) inhibitors, such as rapamycin, are widely used post LT. DATA SOURCES: In this review, we focused on the anti-cancer activities and metabolic side effects of rapamycin after LT. The literature available on PubMed for the period of January 1999-September 2022 was reviewed. The key words were rapamycin, sirolimus, liver transplantation, hepatocellular carcinoma, diabetes, and lipid metabolism disorder. RESULTS: Rapamycin has shown excellent effects and is safer than other immunosuppressive regimens. It has exhibited excellent anti-cancer activity and has the potential in preventing hepatocellular carcinoma (HCC) recurrence post LT. Rapamycin is closely related to two long-term complications after LT, diabetes and lipid metabolism disorders. CONCLUSIONS: Rapamycin prevents HCC recurrence post LT in some patients, but it also induces metabolic disorders. Reasonable use of rapamycin benefits the liver recipients.